Hunyuan Multimodal Algorithm Researcher… at Tencent · Palo Alto

Summary: Tencent is a leading technology company, and they are seeking a Hunyuan Multimodal Algorithm Researcher Intern. The role involves conducting research and development of Omni multimodal large models and optimizing model performance to ensure competitiveness in the field. Responsibilities: - Conduct research and development of Omni multimodal large models, including the design and construction of training data, foundational model algorithm design, optimization related to pre-training/SFT/RL, model capability evaluation, and exploration of downstream application scenarios - Scientifically analyze challenges in R&D, identify bottlenecks in model performance, and devise solutions based on first principles to accelerate model development and iteration, ensuring competitiveness and leading-edge performance - Explore diverse paradigms for achieving Omni-modal understanding and generation capabilities, research next-generation model architectures, and push the boundaries of multimodal models Required Qualifications: - Bachelor's degree (full-time preferred) or higher in Computer Science, Artificial Intelligence, Mathematics, or related fields; graduate degrees are prioritized - Hands-on experience in large-scale multimodal data processing and high-quality data generation is highly preferred - Solid foundation in deep learning algorithms and practical experience in large model development; familiarity with Diffusion Models and Autoregressive Models is advantageous - Proficiency in underlying implementation details of deep learning networks and operators, model tuning for training/inference, CPU/GPU acceleration, and distributed training/inference optimization; practical experience is a plus - Participation in ACM or NOI competitions is highly valued - Strong learning agility, communication skills, teamwork, and curiosity Preferred Qualifications: - Hands-on experience in large-scale multimodal data processing and high-quality data generation - Familiarity with Diffusion Models and Autoregressive Models - Publication in top-tier conferences or experience in cross-modal (e.g., audio-visual) research - Practical experience in model tuning for training/inference, CPU/GPU acceleration, and distributed training/inference optimization - Participation in ACM or NOI competitions Required Skills: Deep Learning Algorithms, Large Model Development, Multimodal Data Processing Important Skills: Model Tuning Nice-to-Have Skills: Learning Agility, Curiosity, Communication Skills, Teamwork Benefits: 1 hour of paid sick leave for every 30 hours worked, Up to 13 paid holidays throughout the calendar year, Eligible to enroll in the Company-sponsored medical plan